Intrinsically Motivating Employees’ Online Knowledge Sharing:

Understanding the Effects of Job Design

L. G. Pee & J. Lee

Forthcoming in International Journal of Information Management

Abstract

The knowledge management literature emphasizes intrinsic motivation in promoting

employees’ knowledge sharing due to its consistently positive and lasting effect. Yet, how

intrinsic motivation to share knowledge can be nurtured remains elusive and it is often left to

random development. This study examines how job design, which determines the conditions

in which employees develop and function, influences their intrinsic motivation to share

knowledge. A model that specifies the effect of different job design characteristics and

clarifies the underlying mechanism through which job design affects intrinsic motivation is

developed. Data collected in a survey of 255 employees supported the model. Implications of

the findings for research and practice are discussed.

Keywords: Online knowledge sharing, intrinsic motivation, job design characteristics,

affective commitment

Cite as: L. G. Pee and J. Lee (2015) Intrinsically Motivating Employees‘ Online Knowledge Sharing: Understanding the Effects of Job Design, International Journal of Information Management, 35 (6), pp. 679-690

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Intrinsically Motivating Employees’ Online Knowledge Sharing:

Understanding the Effects of Job Design

L. G. Pee & J. Lee

Forthcoming in International Journal of Information Management

1. Introduction

Knowledge is the basis of many business processes and activities in organizations (Grant

1996). Knowledge sharing among employees creates opportunities for learning, application,

and creation of new knowledge, which in turn reduce costs of production, improve

organizational performance, and enhance innovation capability (Wang and Noe 2010; Wang

and Wang 2012). There is therefore a strong managerial interest in promoting knowledge

sharing.

Many organizations encourage online knowledge sharing because it facilitates the

efficient flow and wide distribution of knowledge among employees, thereby amplifying the

benefits of knowledge sharing. However, promoting online knowledge sharing is also more

challenging. The oft-cited reasons for not sharing knowledge, such as costs of codifying

knowledge (i.e., time and effort), perceived lack of personal benefit, lack of trust, and fear of

losing knowledge power (Kankanhalli et al. 2005; Wang and Noe 2010), are exacerbated in

online knowledge sharing. With regard to costs, online knowledge sharing typically requires

employees to codify their knowledge in the form of composed texts. With regard to perceived

benefit and trust, it is difficult to control how knowledge shared online is applied as it

resembles a public good that could be exploited by any other employee regardless of whether

the employee contributed to its provision (Cabrera and Cabrera 2002); The lack of

reciprocation by beneficiaries is more difficult to detect online; The knowledge shared may

be accessible to people whom the knowledge source do not trust. Employees may also

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perceive a greater loss of knowledge power as knowledge shared online is stored

electronically and remains accessible long after it is posted.

Among various antecedents of online knowledge sharing, motivation has been studied

extensively (Bartol and Srivastava 2002; Bock and Kim 2002; Bock et al. 2005; Gagné 2009;

Hau et al. 2013; Hsu 2006; Lin 2007; Osterloh and Frey 2000). Extrinsic motivation focuses

on the goal-driven outcomes of sharing knowledge (e.g., rewards, career advancement), while

intrinsic motivation emphasizes inherent enjoyment (Lin 2007). Although both extrinsic and

intrinsic motivations have been found to be significant, it is widely agreed that intrinsic

motivation has a stronger, more stable, and more sustainable effect. In contrast, extrinsic

motivation has shown positive (e.g., Kankanhalli et al. 2005), insignificant (e.g., Lin 2007;

Seba et al. 2012), and even negative effects (e.g., Bock et al. 2005). The inconsistent findings

indicate that extrinsic motivation may secure only temporary compliance, has an indirect

effect, and needs to fit with employees’ expectations to work (Bock et al. 2005; Wasko and

Faraj 2000; Wei et al. 2010). Mandating knowledge sharing through the promise of a reward

or threat of punishment often results in satisficing in which employees only provide

knowledge meeting the minimum necessary quantity and quality (Gagné 2009). In

comparison, intrinsic motivation has a well-established positive effect which has been shown

to be stronger than that of extrinsic motivation (e.g., Foss et al. 2009; Hau et al. 2013; Hung

et al. 2011; Lin 2007; Natalia et al. 2009). Intrinsic motivation provides enjoyment and

satisfaction in the activity of knowledge sharing itself, leading to a more enduring behavior

(Osterloh and Frey 2000). It can also overcome the multiple-task problem, in which

employees who hold back their knowledge cannot always be objectively identified and

sanctioned and sharing therefore cannot be fully assured contractually (Osterloh and Frey

2000).

Although many studies conclude that employees should be intrinsically motivated to

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share knowledge, how intrinsic motivation can be nurtured remains elusive. This is partly

because prior KM studies have focused more on the effects of intrinsic motivation than its

sources. The gap may also be due to the traditional view that intrinsic motivation is a natural

inclination or inherent disposition. Similarly, KM researchers have noted that intrinsic

motivation may be more difficult to change compared to extrinsic motivation (e.g., Osterloh

and Frey 2000). However, more contemporary psychology research has begun to recognize

that intrinsic motivation may be affected by the conditions in which individuals develop and

function and its maintenance and enhancement require supportive conditions (Ryan and Deci

2000). This study examines job design as one potential condition affecting employees’

intrinsic motivation to share knowledge.

We focus on job design in view of its relevance, motivational potential, managerial

focus, and prior evidence. First, job design determines how employees carry out their work

and it is constantly being experienced by employees in daily work. It leaves a deep imprint on

the psychological states of employees (Hackman and Oldham 1976) and is therefore likely to

have a pervasive impact on intrinsic motivation by shaping the conditions in which

employees develop and function (Ryan and Deci 2000). Second, job design has been shown

to motivate job performance (Garg and Rastogi 2006; Hackman and Oldham 1976;

Humphrey et al. 2007). This indicates its potential in influencing employees’ intrinsic

motivation to share knowledge. Nevertheless, we note that online knowledge sharing is

largely an extra-role, pro-social, organizational citizenship behavior rather than an obligatory

job responsibility. The findings of job performance studies therefore cannot be assumed to be

directly applicable and a more direct examination in the context of knowledge sharing is

necessary. Third, job design is amenable to active management, through varying skill variety,

task identity, job autonomy, task feedback, and task significance (Hackman and Oldham

1976). It is therefore practically relevant to determine the extent to which it is effective in

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promoting the intrinsic motivation to share knowledge online. Fourth, some of the job design

characteristics have been shown to influence intrinsic motivation to share knowledge.

Notably, Foss et al. (2009) found that job autonomy had a significant effect. It is worthwhile

to extend this line of inquiry by examining the other job characteristics, as well as

understanding how job design influences intrinsic motivation by explaining the underlying

mechanism.

Based on our review of the literature on intrinsic motivation, job design, and

knowledge management, we propose that affective commitment mediates the impact of job

design on employees’ intrinsic motivation to share knowledge online. Affective commitment

has been shown to drive employees to go beyond their call of duty to engage in extra-role,

organizational citizenship behavior (Meyer et al. 2002). As discussed earlier, online

knowledge sharing involves significant costs and is voluntary rather than obligatory. Further,

job design research suggests that job design affects affective commitment (Warr 1987) while

motivation researchers posit that affective commitment is an energizing force for intrinsically

motivated behavior (Meyer et al. 2004). These indicate that affective commitment could be

an important and relevant factor explaining the underlying mechanism through which job

design influences employees’ intrinsic motivation to share knowledge.

In sum, the research objectives of this study are 1) extend prior research (e.g., Foss et

al. 2009) by examining the impact of all five job design characteristics simultaneously and 2)

better understand how job design influences employees’ intrinsic motivation to share

knowledge online by proposing and assessing a model that accounts for the mediating effect

of affective commitment. As summarized in Table 1, this study also advances research and

practice by considering intrinsic motivation to share knowledge as being amenable to

purposeful management rather than something that can only be left to random development.

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Table 1. Preview of Study Contributions

State of the Literature This Study Relevance

Theory/Empirics PracticeIntrinsic motivation is more difficult to change compared to extrinsic motivation (e.g., Osterloh and Frey 2000).

Intrinsic motivation to share knowledge online is influenced by job design, which is amenable to purposeful management.

Job autonomy (a job design characteristic) influences intrinsic motivation to share knowledge (Foss et al. 2009).

- Job autonomy as well as other job characteristics have significant effects

- The effects of job characteristics on intrinsic motivation to share knowledge online are mediated by affective commitment

Job autonomy has a positive linear effect (Foss et al. 2009).

Different job design characteristics have different effects, which can be linear or curvilinear.

2. Conceptual Background

2.1 Review of Literature on Intrinsic Motivation to Share Knowledge

Employees who are intrinsically motivated to share knowledge find the activity itself

interesting, enjoying, and stimulating (Foss et al. 2009) and engage in sharing for its own

sake (Lin 2007). Intrinsic motivation can be directed to the activity’s flow, a self-defined goal,

or obligations of personal and social identities (Ryan and Deci 2000). For example, through

knowledge sharing, employees may derive pleasure from demonstrating altruism by helping

others. They may also gain satisfaction from recognizing their ability to provide valuable

knowledge that is useful to the organization (Kankanhalli et al. 2005).

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Table 2. Studies on Employees’ Intrinsic Motivation (IM) to Share Knowledge

Study Findings Related to IM Factors Studied alongside IM Sample

Cabrera et al. (2006)

- IM (intrinsic reward) knowledge sharing

- Big five personality - Extrinsic rewards - Job autonomy - Perceived availability of KM

systems - Perceived support from

colleagues - Quality of the contents in KM

systems - Role breadth self-efficacy - Value-based commitment

372 employees in a multinational IT company

Foss et al. (2009)

- Autonomy IM - IM receiving of knowledge - IM sending of K

- External motivation - Introjected motivation

263 employees in a company in Germany

Hau et al. (2013)

- IM (enjoyment) tacit knowledge sharing intention

- IM (enjoyment) explicit knowledge sharing intention

- Reciprocity - Social capital

2010 employees in seven Korean firms

He and Wei (2009)

- IM (enjoyment in helping) contribution belief contribution intention

- Reciprocity - Social relationship

201 employees in an IT company

Hung et al. (2011)

- IM Intention to share knowledge using electronic repositories

- IM perceived ease of use

- Reciprocity - Reputation

225 employees of 20 organizations in Taiwan

Kankanhalli et al. (2005)

- IM (enjoyment in helping) electronic repository usage by knowledge contributors

- Codification effort - Generalized trust - Organizational reward - Identification - Reciprocity - Pro-sharing norms - Knowledge self-efficacy

150 employees in public organizations in Singapore

Lin (2007) IM (enjoyment in helping) knowledge sharing intention

- Expected organizational rewards

- Knowledge self-efficacy - Reciprocal benefit

172 employees in 1000 largest firms in Taiwan

Reinholt et al. (2011)

- IMknowledge provision - IM * knowledge-sharing ability

knowledge provision - IM * knowledge-sharing ability *

network centrality knowledge provision

- Knowledge-sharing ability - Network centrality

705 employees in an consulting firm in Denmark

Yan and Davison (2013)

- IM (enjoyment in helping) Web 2.0 usage for knowledge contributing

- Web 2.0 usage for knowledge seeking IM (enjoyment in helping)

- Flow - Sense of self-worth

232 employees in 14 organizations in China

Intrinsic motivation, which is experienced as self-endorsed rather than due to external

pressure or regulation (Reinholt et al. 2011), is especially relevant in the sharing of high-

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quality knowledge because it is a discretionary behavior that can only be encouraged and

facilitated rather than forced (e.g., Bock et al. 2005). Indeed, the salience of intrinsic

motivation on knowledge sharing is well established and supported by consistent and strong

empirical evidence (see Table 2). Despite its significance, most studies have modeled

intrinsic motivation as an exogenous factor. Much less attention has been given to factors

influencing its development. An exception is a study that sought to explore the behavioral

transfer from knowledge seeking to knowledge sharing (Yan and Davison 2013). The study

found that knowledge seeking can provide information about other employees’ enjoyment,

thereby influencing one’s intrinsic motivation to share knowledge. Another study has

identified job autonomy as an antecedent of intrinsic motivation (Foss et al. 2009). These

studies indicate that intrinsic motivation to share knowledge could be influenced by the

conditions in which employees develop and function. This study examines job design as one

such condition.

2.2 Job Design Characteristics

The job design model suggests that job characteristics can influence various work outcomes

such as work quality, job satisfaction, absence from work, and turnover (Hackman and

Oldham 1976). The five core job characteristics are skill variety, task identity, job autonomy,

task feedback, and task significance (Hackman and Oldham 1976). Skill variety refers to the

degree to which the job requires a range of different activities in carrying out the work,

involving the use of different skills and talents of the employee (Hackman and Oldham 1976).

Task identity refers to the degree to which the job requires doing a whole and identifiable

piece of work from beginning to end. A job with high task identity requires the employee to

follow through the main stages to “provide a complete unit of product or service” (Hackman

and Oldham 1976, p. 257) instead of just an indistinguishable part. Job autonomy refers to the

degree to which the job provides substantial freedom, independence, and discretion to the

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individual in scheduling the work and in determining the procedures to be used in carrying it

out. In high-autonomy jobs, job outcomes depend more on the employee’s efforts, initiatives,

and decisions rather than on the adequacy of instructions from supervisors or adherence to

standard operating procedures. Task feedback refers to the degree to which carrying out the

work activities required by the job provides the individual with direct and clear information

about the effectiveness of his or her performance. Receiving feedback on one’s performance

is a critical element of feeling competent. Task significance refers to the degree to which the

job has a substantial impact on the lives of other people, whether those people are in the

immediate organization or the world at large. Task significance thus allows the employee to

experience the job as being more meaningful.

3. Theoretical Development

In this study, we develop a model to explain the effects of job design characteristics on

intrinsic motivation to share knowledge online (see Figure 1). Specifically, we propose that 1)

job characteristics influence intrinsic motivation to share knowledge online through affective

commitment, and 2) different job characteristics have different effects, which can be linear or

curvilinear. We develop the overarching job characteristics affective commitment

intrinsic motivation relationship by integrating several theories. A theory that identifies

affective commitment to be a key antecedent of intrinsic motivation is the Integrative Model

of Employee Commitment and Motivation (Meyer et al. 2004); The job characteristics

affective commitment relationship is suggested by the Job Demands-Resources Model

(Bakker and Demerouti 2007) and Warr’s Vitamin Model (Warr 1987); They also provide the

bases for hypothesizing the different effects of different job characteristics. Overall, these

theories pinpoint the mediating role of affective commitment. This study is the first to

integrate these theories to clarify the mechanism though which job design influences

employees’ intrinsic motivation to share knowledge. The rest of this section details the

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development of these relationships and the underpinning theories.

Figure 1. Proposed Model of Intrinsic Motivation to Share knowledge

3.1 Affective Commitment – Intrinsic Motivation Relationship

Intrinsic motivation is theorized as being influenced by affective commitment in the

Integrative Model of Employee Commitment and Motivation (Meyer et al. 2004). The model

posits that employees’ goal regulation, which is a motivational mindset that can be intrinsic

or extrinsic, is influenced by their commitment (Meyer et al. 2004). Intrinsic goals are more

autonomous, and the resultant behavior is undertaken purely for its own sake (i.e., the activity

itself is enjoyable). Employees who have a strong affective commitment are likely to share

the organization’s values and experience greater intrinsic motivation to pursue goals relevant

to the organization.

Affective commitment refers to an employee’s emotional attachment to, identification

with, and involvement in the organization (Meyer and Allen 1991). Affectively committed

employees feel psychologically bonded to their organization and experience volitional

dedication and responsibility for the wellbeing of the organization (Klein et al. 2012). The

commitment results in a willingness to make trade-offs in favor of the organization when

allocating resources such as time and attention and provides a general direction to behavior.

In the context of online knowledge sharing, affective commitment can help to

overcome the knowledge sharing dilemma as employees become more concerned with the

overall performance of the organization and the collective welfare of all organizational

members rather than focusing solely on individual costs and benefits (Cabrera and Cabrera

2002; Hislop 2003). Although there is still a lack of empirical evidence, the potential

H1 (+)Affective Commitment

Job Characteristics - Skill variety (H2, ∩) - Task identity (H3, ∩) - Job autonomy (H4, +) - Task feedback (H5, +) - Task significance (H6, +)

Intrinsic Motivation to Share Knowledge

Online

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influence of affective commitment on intrinsic motivation has been pointed out in KM

research. For instance, Hislop (2003) developed a psychological contract model of

knowledge sharing which proposes that employees’ motivation to share knowledge is shaped

by their level of organizational commitment. Storey and Quintas (2001) suggest that

knowledge workers with high levels of organizational commitment are less likely to leave,

more likely to be highly motivated, and will probably be more willing to provide extra

discretionary effort such as sharing their knowledge within the organization. In line with this,

Jarvenpaa and Staples (2001) advocate that greater commitment engenders the belief that the

organization has rights to the knowledge that one has created or acquired and could drive the

use of electronic media for sharing. This study tests the hypothesis empirically:

H1: Affective commitment towards organization increases employees’ intrinsic motivation to

share knowledge.

3.2 Effects of Job Characteristics

The effects of job characteristics are proposed based on the Job Demands-Resources Model

and Warr’s Vitamin Model. These theories suggest that 1) job characteristics influence

affective commitment, and 2) different job characteristics have different effects.

The job demands-resources model categorizes job characteristics into two types. Job

demands are aspects of the job that require sustained physical or mental effort and are

therefore associated with certain physiological and psychological costs. High job demands

exhaust employees’ mental and physical resources and therefore lead to the depletion of

energy and health problems. In contrast, job resources refer to aspects of the job that are

functional in achieving work goals, deal with job demands, and stimulate personal growth

and development. They foster engagement, organizational commitment, and extra-role

performance (Bakker and Demerouti 2007). Bakker and Demerouti (2007) suggests that job

autonomy, task feedback, and task significance are job resources that fulfill the basic human

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need for autonomy, feeling of competence, and social relatedness. Decision latitude satisfies

the need for autonomy; Constructive task feedback fosters learning and thus increases job

competence; Task significance increases the perceptions of social impact and social worth

and thereby fulfills the need for relatedness (Grant 2008). In contrast, skill variety and task

identity demonstrate features of job demands. A job that requires diverse skills and talents

calls for greater mental effort and can become taxing (Chen and Chiu 2009; Xie and Johns

1995); Jobs with high task identity demands employees to complete a whole and identifiable

output and the increased accountability can create stress when it exceeds employees’ limit

(Hochwarter et al. 2005; Lin and Hsieh 2002).

The Warr’s Vitamin Model (Warr 1987) proposes that job demands have negative

effects on employees’ affective wellbeing, including affective commitment, in a way that is

analogous to the effects that some vitamins have on physical health. In general, deficiency in

vitamins is detrimental and vitamin intake can initially improve health. However, an overdose

of vitamins may lead to toxic concentration which causes a decline in health. Likewise, the

absence of job demands impairs employees’ affective wellbeing and their presence has a

beneficial effect initially (segment A of Figure 2). Beyond a certain required level, further

increase in job demands (segment B) is harmful and impairs affective wellbeing. This n-

shaped curvilinear effect of job characteristics is named the additional decrement effect. The

additional decrement effect of job demands can be explained by the activation theory, which

states that mental arousal is necessary for effective functioning and a certain level of

activation is needed to motivate work behavior and performance (Scott 1966). Employees

seek activation through different types of simulation, including variation, complexity, and

novelty. When there is an absence of activation, they may experience boredom, a lack of

alertness, and dulling of the senses. However, too much stimulation that goes beyond the

upper limit of activation can generate emotional stress.

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Figure 2. Additional Decrement Effect in Warr’s Vitamin Model

3.2.1 Effects of Job Demands

Warr’s Vitamin model suggests that the job demands of skill variety and task identity have a

curvilinear effect on affective commitment. With regard to skill variety, Fullagar and

Kelloway (2009) observed that employees are likely to feel bored with activities that do not

challenge their skills. Wiesner et al. (2005) found that employees working on jobs with low

skill variety tend to feel depressed. Such employees are unlikely to develop strong affective

commitment for their organization. It has been shown that enhancing skill variety through

practices such as job rotation improves employees’ affective commitment (Humphrey et al.

2007). However, researchers note that very high skill variety may deplete employees’ mental

resources and lead to mental overload and increase job pressure (Chen and Chiu 2009; Xie

and Johns 1995). The mental strain is likely to decrease affective commitment. This study

assesses the full spectrum of skill variety’s impact by hypothesizing an n-shaped effect:

H2: When the level of skill variety is very low or very high, employees’ affective commitment

is lower than that when skill variety is moderate.

Pedrini et al. (2009) found that employees working in jobs with low task identity feel

that they lack personal accomplishment. It has been observed that feelings of boredom and

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meaninglessness are prevalent among employees with low task identity (Gemmill and Oakley

1992). These imply that the level of affective commitment will be low when task identity is

low. Increasing task identity has been found to improve organizational commitment (Dunham

et al. 1994). However, when task identity is very high, employees may feel solely

accountable for the outcome of their work, resulting in stress. In support of the curvilinear

effect, Lin and Hsieh (2002) found that task identity has an n-shaped relationship with

organizational commitment:

H3: When the level of task identity is very low or very high, employees’ affective commitment

is lower than that when task identity is moderate.

3.2.2 Effects of Job Resources

The job resources of job autonomy, task feedback, and task significance are expected to have

a positive linear effect on affective commitment. Jobs with low autonomy require employees

to follow rigid rules and procedures and provide little flexibility for employees to structure

work according to their circumstances and preferences. These employees often feel that their

use of judgment at work and personal initiative are suppressed, which may evoke opposition

and resistance and lead to the development of negative attitudes (Naus et al. 2007). Increasing

job autonomy should enhance perceived personal control, which is the amount of control that

individuals believe they have over their environment to make it less threatening or more

rewarding. Personal control is a basic human need that has been shown to have strong effect

on wellbeing (Sels et al. 2004). This implies that increasing job autonomy facilitates the

development of affective commitment:

H4: Job autonomy is positively related to affective commitment towards organization.

Task feedback may be provided by coworkers, customers, supervisors, and the work

activity itself. Effectiveness of performance may also be gleaned by comparing available

information about performance with job description and goals. Feedback helps to alleviate

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uncertainty and has been found to reduce employee perceptions that organizational decisions

are politically driven, potentially uncontrollable, threatening, or unfair (Rosen et al. 2006).

Perceptions of politics influence employees’ morale, as reflected in low job satisfaction and

organizational commitment. Employees with low morale are likely to reduce the time and

effort put into meeting organizational objectives, thus resulting in lower levels of

organizational citizenship behavior. Task feedback also provides information for employees

to learn about their proximity to goal accomplishment and enhances the experienced

meaningfulness of their job (Humphrey et al. 2007). Pursuing meaning is an important goal in

one’s life and experiencing meaning can promote wellbeing (King and Napa 1998).

H5: Task feedback is positively related to affective commitment towards organization.

Grant (2012) links task significance to pro-social behavior, which refers to the act of

freely giving one’s time, knowledge, or skills for the benefit of others. When employees

perceive their jobs as high in task significance, they experience their work as more

meaningful (i.e., more purposeful and valuable). This experience of meaningfulness can

motivate employees to invest additional time and energy at work. Further, employees

working in jobs with high task significance tend to believe that their actions benefit others

(social impact) and are valued by others (social worth) (Grant 2008). Such employees are

likely to develop positive affective commitment towards their organization that has provided

them with the legitimacy to do so.

H6: Task significance is positively related to affective commitment towards organization.

3.3 Mediating Effect of Affective Commitment

Taken together, the Integrative Model of Employee Commitment and Motivation, Job

Demands-Resources Model, and Warr’s Vitamin Model suggest that affective commitment

mediates the effect of job characteristics on employees’ intrinsic motivation to share

knowledge online. The Integrative Model of Employee Commitment and Motivation suggests

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affective commitment intrinsic motivation, and the other two models suggest job

characteristics affective commitment. Affective commitment is also strongly relevant in

online knowledge sharing as it shifts employees’ attention away from individual costs and

benefits and towards the welfare of their organizations (Cabrera and Cabrera 2002; Hislop

2003). Accordingly, we hypothesize that affective commitment is an important underlying

mechanism through which job characteristics influence intrinsic motivation. This study is the

first to hypothesize and test the mediation:

H7: The effects of job characteristics on employees’ intrinsic motivation to share knowledge

online are mediated by affective commitment.

3.4 Control Effects and Variables

Since the effect of intrinsic motivation on knowledge sharing behavior is an important

premise of this study and it is already well established, the relationship was controlled for in

our analysis. Other control variables are age, education, gender, job level, and job tenure.

4. Research Method

Data for assessing the proposed model were collected in a survey. This section describes the

development of survey instrument and data collection.

4.1 Construct Operationalization

The survey instrument was developed in two steps: First, scales that could potentially

measure the constructs were identified from prior studies. Next, a pilot survey involving 211

full-time employees was conducted to identify possible improvement to the measures as well

as procedure. Based on the results of the pilot survey, we revised the measure of task

feedback to clarify that the focus is on constructive feedback. This is in line with the job

demands-resources model which specified constructive feedback to be a job resource (Bakker

and Demerouti 2007) and removes any ambiguity in the valence of feedback in the measure.

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Table 3. Construct Operationalization

Skill Variety (adapted from Morris and Venkatesh 2010) To what extent… SV1: ...does your job have variety? Having variety means you are required to do many different things at work, using a variety of your skills and talents. SV2: ...does your job require you to use a number of complex or high-level skills? SV3: ...is your job complex and non-repetitive?

Task Identity (adapted from Morris and Venkatesh 2010) To what extent… TI1: ...does your job involve doing a whole and identifiable piece of work? A whole and identifiable piece of work means a complete piece of work that has an obvious beginning and end rather than only a small part of the overall piece of work TI2: ...does your job provide you the chance to completely finish the pieces of work you begin? TI3: ...is your job arranged so that you can do an entire piece of work from beginning to end?

Job Autonomy (adapted from Morris and Venkatesh 2010) To what extent does your job … JA1: …have autonomy? Having autonomy means that you are allowed to decide on your own how to go about doing the work. JA2: ... give you opportunity for independence and freedom in how you do the work? JA3: ... give you chances to use your personal initiative and judgment in carrying out the work?

Task Feedback (adapted from Morris and Venkatesh 2010) To what extent does your job provides… TF1: clues about how well you are doing – aside from any constructive feedback that coworkers or supervisors may provide? TF2: chances for you to figure out how well you are doing your job? TF3: constructive feedback of how you have performed?

Task Significance (adapted from Morris and Venkatesh 2010) To what extent… TS1: ...is your job significant in general? A significant job means that the results of your work are likely to significantly affect the lives or wellbeing of other people. TS2: ...is your job one where a lot of other people can be affected by how well the work gets done? TS3: ...is your job significant and important in the broader scheme of things?

Affective Commitment (adapted from Rhoades et al. 2001) To what extent… AF1: …would you be happy to work at your organization until you retire? AF2: …do you feel that the problems faced by your organization are also your problems? AF3: …do you feel a sense of belonging to your organization? AF4: …do you feel personally attached to your organization? AF5: …does working at your organization have a great deal of personal meaning to you? AF6: …are you proud to tell others that you work at your organization?

Intrinsic Motivation (adapted from Wasko and Faraj 2005) To what extent do you… IM1: … enjoy sharing knowledge with others through your organization’s electronic knowledge repositories? IM2: … enjoy helping others by contributing to your organization’s electronic knowledge repositories? IM3: … feel good to help someone else by contributing to your organization’s electronic knowledge repositories? IM4: … experience pleasure by contributing to your organization’s electronic knowledge repositories?

Knowledge Sharing (adapted from Hsu et al. 2007) KC1: On average, how much time do you spend on creating each submission to your organization’s electronic knowledge repositories? KC2: On average, how often do you create new submissions (rather than update existing ones) to your organization’s electronic knowledge repositories? KC3: To what extent do you contribute knowledge to many different topics rather than specific topics on your organization’s electronic knowledge repositories?

* All items were measured with seven-point Likert scale

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The operationalization of constructs is shown in Table 3. To capture low and high

levels of job characteristics, we followed Janssen (2001) and worded all the measurement

items in the question form (e.g., “to what extent does your job have variety?”), along with a

scale anchored by “not at all” – “moderate” – “to a very great extent”.

4.2 Data Collection

The target population of this study is employees working in organizations that facilitate

online knowledge sharing. We focus on employees occupying professional and managerial

positions because their work is likely to be knowledge-intensive and they are typically the

anticipated participants of online knowledge sharing in organizations. The sampling and

survey were conducted through a research company, which had a panel of 88,856 employees.

The company randomly selected 553 employees occupying professional and managerial

positions and invited them to complete the online survey. The survey included two filter

questions: the first question requested respondents to indicate the types of information system

available for their use in their organizations; the second question asked respondents to

indicate their job position. Only those employees working in organizations with online

knowledge sharing systems and those occupying professional or managerial positions at the

time of the survey were invited to complete the rest of the survey. Those who completed the

survey could opt to receive reward points which could be accumulated and exchanged for

items of their choice from the research company.

We received 255 completed responses from qualified respondents, yielding a response

rate of 46.1%. We examined the data to assess potential issues related to nonresponse bias

and common method bias. To assess non-response bias, the demographic characteristics of

respondents and non-respondents were compared. We did not find statistically significant

differences in age (t=0.23, p=0.82), level of education (t=0.81, p=0.42), organization size (t=-

0.27, p=0.79), and job tenure (t=0.25, p=0.80), suggesting that non-response bias is not an

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issue. To assess common method bias, the widely used Harman’s one-factor test was

conducted. The largest factor extracted did not explain more than 50 percent of the variance,

indicating that common method bias is unlikely.

4.3 Sample Demographics

The characteristics of the survey respondents are summarized in Table 4. The majority of the

respondents are male (64.7%) between 30 to 49 years old (62.7%) and attained a Bachelor

degree (72.5%). About half of them were working in professional positions (60.8%) in

organizations with more than 1000 employees (45.9%). Most of them had been with their

organizations for more than five years (63.1%).

Table 4. Demographic Analysis (n=255)

Characteristic Value Frequency Percent* Cumulative%Gender Female 90 35.3 100.0 Male 165 64.7 64.7Age (years) 20-29 56 22.0 22.0

30-39 83 32.5 54.540-49 77 30.2 84.750-59 30 11.8 96.5>60 9 3.5 100.0

Education Professional Certificate 44 17.3 17.3Bachelor 185 72.5 89.8

Master 4 1.6 91.4PhD 22 8.6 100.0

Job Position Chief Executive Officer/ President 4 1.6 1.6Senior Manager (COO, CFO) 53 20.8 22.4

Division/ Department Manager 34 13.3 35.7 Middle Manager 9 3.5 39.2

Professional 155 60.8 100.0Organization Size (person) 51-100 26 10.2 10.2

101-200 24 9.4 19.6 201-300 17 6.7 26.3 301-400 16 6.3 32.5

401-500 11 4.3 36.9501-1000 44 17.3 54.1>1001 117 45.9 100.0

Job Tenure (year) < 1 22 8.6 8.61-2 19 7.5 16.13-5 53 20.8 36.96-9 60 23.5 60.410-15 39 15.3 75.7>15 62 24.3 100.0

*Percentages for a characteristic may not sum to 100 due to rounding.

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5. Data Analysis

The relationship between affective commitment, intrinsic motivation to share knowledge, and

knowledge sharing behavior were analyzed with Partial Least Square (PLS) regression, a

structural equation modeling approach that allows the simultaneous assessment of the

measurement and structural relationships. PLS is chosen because it is able to analyze

formative constructs. In this study, knowledge sharing was measured formatively, in terms of

frequency, time spent, and variety of topics contributed. Unlike reflective measures, they tap

into different themes and are neither expected to covary nor interchangeable.

The linear and curvilinear effects of job characteristics were estimated using a three-

step hierarchical polynomial regression. Control variables were entered in the first step,

followed by the job characteristics. Quadratic terms were entered in the final step to estimate

curvilinear effects, while controlling for the lower-order effects as required in polynomial

regression. All variables were standardized before creating the quadratic terms to reduce

multicollinearity between linear and quadratic terms (Aiken and West 1991).

The mediating effect of affective commitment was assessed by Sobel test to see

whether the reduction in variance in intrinsic motivation explained by job characteristics

before and after controlling for affective commitment is significant. Detailed results of these

tests are presented next.

5.1 Measurement Reliability and Validity

The survey instrument was tested for indicator reliability, construct reliability, convergent

validity, and discriminant validity (Götz et al. 2010). Indicator reliability was assessed by

examining item loadings. We observed that all loadings were above the recommended value

of 0.70. Construct reliability was estimated using Cronbach’s alpha coefficient and composite

reliability measure. All constructs had scores above the threshold of 0.70 (see Table 5).

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Convergent validity was assessed by examining average variance extracted (AVE) by each

construct (see Table 6). All AVEs were above 0.50 and therefore satisfactory. The

discriminant validity of a construct was assessed by examining whether its AVE is larger than

the squared correlations with other constructs. We found that all constructs had adequate

discriminant validity. Overall, all measures had adequate reliability and validity.

Table 5. Reliability and Distribution Statistics

Construct Cronbach’s

Alpha CompositeReliability

Average VarianceExtracted

Mean StandardDeviation

Skill variety (SV) 0.84 0.91 0.76 3.50 1.32

Task identity (TI) 0.82 0.89 0.72 2.99 1.09

Job autonomy (JA) 0.89 0.93 0.82 3.63 1.46

Task feedback (TF) 0.84 0.90 0.76 3.24 1.09

Task significance (TS) 0.91 0.94 0.84 3.19 1.31

Affective commitment (AC) 0.91 0.93 0.70 3.63 1.26

Intrinsic motivation (IM) 0.97 0.97 0.91 3.79 1.32

Knowledge sharing (KS) N.A. N.A. N.A. 4.39 1.44

Table 6. Square Root of AVE vs. Correlation

SV TI JA TF TS AC IM

Skill variety (SV) 0.87*

Task identity (TI) 0.47 0.85

Job autonomy (JA) 0.44 0.45 0.91

Task feedback (TF) 0.48 0.46 0.52 0.87

Task significance (TS) 0.44 0.43 0.51 0.49 0.92

Affective commitment (AC) 0.43 0.42 0.49 0.61 0.54 0.83

Intrinsic motivation (IM) 0.35 0.31 0.42 0.38 0.42 0.58 0.95

Knowledge sharing (KS) 0.54 0.36 0.50 0.43 0.49 0.50 0.58

* Bold values are square root of AVEs

5.2 Tests of Hypotheses

Results of hypotheses testing are summarized in Table 7. Affective commitment had a

significant effect on intrinsic motivation to share knowledge online (i.e., H1 was supported).

Skill variety had an n-shaped curvilinear effect on affective commitment (i.e., H2 was

supported). However, contrary to hypothesis H3, task identity did not have a significant effect

on affective commitment. Job autonomy, task feedback, and task significance were found to

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be positively related to affective commitment (i.e., H4, H5, and H6 were supported) . The job

characteristics explained 50% of the variance in affective commitment. Affective

commitment, in turn, explained 34% of the variance in intrinsic motivation to share

knowledge. Together, affective commitment and intrinsic motivation explained 39% of the

variance in knowledge sharing behavior.

Table 7. Results of Hypothesis Testing

Partial least squares regression Effect Path P-Value R2 Result AF IM 0.58** 0.003 0.34 H1 is supported IM KS 0.45** 0.004

0.39 Control relationships are significant AF KS 0.24** 0.003

Polynomial regression (dependent variable: affective commitment)

Effect Step 1

R2=0.003 Step 2

R2=0.45 Step 3

R2=0.50Result

Beta P-value Beta P-value Beta P-value Control variables are not significant Age -0.04 0.668 -0.09 0.217 -0.06 0.472

Education -0.03 0.753 -0.07 0.256 -0.05 0.446Gender -0.07 0.465 -0.04 0.534 -0.04 0.538Job position 0.00 0.970 -0.13 0.074 -0.12 0.088Organization tenure -0.03 0.758 -0.05 0.498 -0.06 0.450Skill variety (SV) -0.19 0.056 -0.10 0.372 Control linear effects are

not significant Task identity (TI) -0.06 0.462 -0.10 0.296Job autonomy (JA) 0.31*** <0.001 0.30** 0.002 H4 is supported Task feedback (TF) 0.57*** <0.001 0.49*** <0.001 H5 is supported Task significance (TS) 0.33*** <0.001 0.38*** <0.001 H6 is supported SV2 -0.28** 0.003 H2 is supported TI2 0.09 0.263 H3 is not supported JA2 0.09 0.322 Control curvilinear effects

are not significant TF2 0.15 0.055TS2 -0.10 0.274SV * TI 0.04 0.709SV * JA 0.13 0.283SV * TF 0.16 0.214SV * TS 0.03 0.852TI * JA -0.14 0.146TI * TF -0.15 0.190TI * TS 0.05 0.624JA * TF -0.06 0.492JA * TS 0.01 0.912TF * TS -0.11 0.340Sobel test for assessing mediation

Job Characteristic Sobel P-value Result Skill Variety2 3.99* <0.05 H7 is supported Job autonomy 4.42* <0.05 Task feedback 3.33* <0.05 Task significance 2.55* <0.05 Significant at **p<0.01, ***p<0.001

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In the Sobel test, there is significant reduction in variance in intrinsic motivation

explained by the job characteristics of skill variety, job autonomy, task feedback, and task

significance (see Table 7), supporting the hypothesis that the effect of job characteristics are

mediated by affective commitment (i.e., H7 was supported).

The curvilinear effect of skill variety is plotted in Figure 3. It can be seen that as skill

variety increases towards the sample mean, affective commitment increases. However, as

skill variety increases beyond the mean, affective commitment begins to decrease. Given the

positive relationship between affective commitment and intrinsic motivation, knowledge

sharing will begin to decrease as well.

Figure 3. Curvilinear Effect of Skill Variety

6. Discussion

This study sought to examine how all five job design characteristics influence employees’

intrinsic motivation to share knowledge online. Supporting the proposed model, we found

that job characteristics influence intrinsic motivation through impacting affective

commitment. The job demand of skill variety has an n-shaped curvilinear effect while the job

resources of job autonomy, task feedback, and task significance have a positive linear effect.

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The implications of the proposed model and findings are discussed in the following

subsections.

Unexpectedly, the curvilinear effect of task identity was not significant. To a certain

extent, this contradicts the finding of a prior study that task identity has a significant n-shaped

curvilinear effect on organizational (rather than affective) commitment (Lin and Hsieh 2002).

Rather than concluding that task identity does not have a significant effect, we believe that it

is necessary to ascertain the effect in further studies. One explanation for the different

findings might be that it is necessary to consider moderators. For instance, personal

characteristics such as growth need strength (Oldham and Hackman 2010) may moderate the

effect of task identity such that employees with little inherent need to grow would not pursue

or respond to the internal “kick” that comes from succeeding on high-identity tasks.

Organizational characteristics such as effort-reward fairness has also been shown to moderate

the curvilinear effect of job demands such that those who perceive reward unfairness feel less

satisfied to intermediate levels of job demands because the unfairness distracts them from the

positive qualities of job demands (Janssen 2001). Accounting for these moderating effects in

further studies may provide a better understanding of the effect of task identity.

6.1 Implications for Theoretical Development and Research

The theoretical contribution of this study is four-fold. First, the proposed model advances

KM research by looking beyond the effects of intrinsic motivation to understand how job

characteristics influence intrinsic motivation. Prior studies have not investigated this, even

though a) intrinsic motivation is an important factor in online knowledge sharing, b) several

theories and researchers suggest that job characteristics potentially have significant effects,

and c) job characteristics are amenable to purposeful management in practice.

Second, this study clarifies that job characteristics influence intrinsic motivation

through affective commitment. This provides a theoretical explanation for the mechanism

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underlying the effects of job characteristics on online knowledge sharing, which is not an

obligatory job behavior. Establishing the mediating role of affective commitment links the

two disparate streams of research on job design and KM and elucidates how job design is

relevant to employees’ knowledge sharing.

Third, the proposed model also identifies the different effects of job demands and job

resources, which can be linear or curvilinear. This provides a nuanced understanding of the

effects of job characteristics, which have been conceptualized and tested predominantly in

linear terms in KM studies. The curvilinear effect of skill variety reveals its paradoxical

negative impact and refines our understanding of the impact of job characteristics on intrinsic

motivation to share knowledge. This study demonstrates that curvilinear effects may be

relevant in understanding knowledge sharing in particular and KM behaviors in general.

Extending this study, future research may investigate whether the mixed results related to

extrinsic motivation can be clarified by considering curvilinear effects.

Fourth, this study is one of the earliest to draw on the theories of Integrative Model of

Employee Commitment and Motivation, Job Demands-Resources Model, and Warr’s

Vitamin Model in KM research. We have demonstrated the relevance of these theories in

explaining online knowledge sharing behavior in organizations, which involves employees

and seeks to promote the flow of job-related knowledge. The explanatory power of the

proposed model demonstrates the theories’ value in enhancing our understanding of

knowledge sharing. The findings also suggest the potential of applying other theories of

organizational behavior. For instance, leadership theories have strong relevance. Ilies et al.

(2005) propose that the transformational leadership style facilitates higher levels of

knowledge sharing. Transformational leaders are seen as considerate, intellectually

stimulating, charismatic, and inspirational by followers. Leaders may be regarded as role

models and motivate employees through social learning (Ilies et al. 2005). In most

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organizations, they also control the allocation of resources and are in a particularly legitimate

position to foster employees’ sense of self-determination and subsequently intrinsic

motivation.

More studies that explore other antecedents can further improve our conceptual

understanding of the sources of employees’ intrinsic motivation to share knowledge. A

theoretical framework that could serve as a basis for this endeavor is the theory of human

motivation developed by Maslow (1943). The theory states that employees have five levels of

needs that have to be satisfied for them to feel motivated: physiological, safety, social, ego,

and self-actualizing. Job characteristics examined in this study contribute to fulfilling social,

ego, and self-actualizing needs but less to physiological and safety needs. Future research can

investigate these two types of need in terms of factors related to KM. With regard to

physiological needs, it has been observed that open-plan office design and water cooler areas

facilitate the flow of knowledge in organizations (e.g., Waring and Bishop 2010). Maslow’s

theory suggests that their effects on KM may be partly explained by their influence on

employees’ intrinsic motivation. As for the safety need, job security may be a salient

antecedent of intrinsic motivation. Sharing knowledge online entails risks to one’s knowledge

power and having job security may motivate employees by addressing the risks directly.

6.2 Implications for Practice

This study shows that, contrary to the prevailing belief, employees’ intrinsic motivation to

share knowledge can be more actively managed in organizations and its development need

not be left to chance. Among the job characteristics, job autonomy, task feedback, and task

significance have positive linear effect and they should therefore be increased to promote

knowledge sharing. Job autonomy may manifest as work scheduling autonomy, work

methods autonomy, and decision-making autonomy (Morgeson and Humphrey 2006). In

practice, one way of increasing job autonomy is through the use of autonomous workgroups,

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where members are allowed to allocate work among themselves, organize schedules, address

customer requirements, and recruit new members. Not only does working in such workgroups

enhance employees’ job autonomy, they have also been found to lead to better coordination,

more expertise, and increased innovation (Cohen et al. 1996). Constructive task feedback

should be clear and understandable, specific to the targeted behavior, and emphasize the

performance of the employee. Feedback should focus on providing information necessary for

improving or maintaining desired performance and avoid references to personal

characteristics of the employee. Feedback could be enhanced by supportive statements, social

praise, constructive criticism, and modeling (London 2003). Task significance may be

increased by clarifying employees’ individual contribution to moral ideals and higher-order

goals such as department or organizational objectives. Managers may also provide more

opportunities for employees to have direct contact with the (internal or external) beneficiaries

of their work to better understand the impact of their work on others (Grant 2008) through

organizing focus groups, public presentations, and other socializing events.

Skill variety has a curvilinear effect such that very low and very high levels of skill

variety have detrimental effects. This has important implications for practice, as employees

working in jobs with high skill variety have the greatest potential to accrue valuable know-

how and experience. They therefore constitute the critical mass of knowledge sharing

participants that would attract other users (Peddibhotla and Subramani 2007). Ironically, the

curvilinear effect suggests that this group may not share as much as the organization would

have hoped. The marginal benefit of skill variety in motivating knowledge sharing decreases

at high levels and disappears at extreme levels. A useful approach for keeping skill variety

optimal is empowering employees to craft their jobs by changing cognitive, task, and

relational boundaries to cope with the demands (Wrzesniewski and Dutton 2001).

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6.3 Limitations and Suggestions for Improvement

A limitation of this study is that the survey was cross-sectional. Conducting a longitudinal

study that measures the independent and dependent variables at different times can provide

stronger evidence for the causal relationships in the proposed model. A longitudinal study

also offers opportunities to advance our research model by incorporating temporal

mechanisms. For example, it will be interesting to examine whether employees’ perception

about job characteristics changes over time and how the change influences their affective

commitment and intrinsic motivation.

It has been suggested that the distribution of a variable may influence the statistical

power of detecting its curvilinear effect (McClelland and Judd 1993). The distribution with

higher statistical power is one where one fourth of the observations are at either extreme of

the variable and the remaining half of the observations is exactly halfway between those two

extremes. In this study, data were collected in a survey and it was therefore not feasible to

manipulate the distribution of job demands. As a result, weak curvilinear effects might have

gone undetected. Future studies may explore the feasibility of conducting experiments to

assess the proposed model in a more controlled setting. If so, it must be noted that over-

sampling extreme observations may produce an inflated estimate of the variance explained.

7. Conclusion

With strong evidence for its prominence in KM, the time is ripe to trace farther back along

the causal chain of intrinsic motivation to share knowledge to examine its antecedents. Our

findings indicate that intrinsic motivation is influenced by job characteristics through

affective commitment and is at least as tenable to management as extrinsic motivation. This

study also highlights the need to be mindful about the diminishing return of increasing skill

variety. Identifying other factors influencing intrinsic motivation can unravel more

Page 28 of 31

approaches for effectively addressing the daunting challenge of motivating employees to

share knowledge online.

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